• Journal of the Korea Society of Computer and Information
• /
• v.24 no.9
• /
• pp.43-49
• /
• 2019

Today, with the development of the internet of things, wearable devices related to personal health care have become widespread. Various global information and communication technology companies are developing various wearable health devices, which can collect personal health information such as heart rate, steps, and calories, using sensors built into the device. However, since individual health data includes sensitive information, the collection of irrelevant health data can lead to personal privacy issue. Therefore, there is a growing need to develop technology for collecting sensitive health data from wearable health devices, while preserving privacy. In recent years, local differential privacy (LDP), which enables sensitive data collection while preserving privacy, has attracted much attention. In this paper, we develop a technology for collecting vast amount of health data from a smartwatch device, which is one of popular wearable health devices, using local difference privacy. Experiment results with real data show that the proposed method is able to effectively collect sensitive health data from smartwatch users, while preserving privacy.

• Journal of Information Processing Systems
• /
• v.15 no.5
• /
• pp.1192-1200
• /
• 2019

Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.

• Journal of Korea Multimedia Society
• /
• v.25 no.2
• /
• pp.197-205
• /
• 2022

The Cyber Physical System(CPS) is an important concept in achieving SMSs(Smart Manufacturing Systems). Generally, CPS consists of physical and virtual elements. The former involves manufacturing devices in the field space, whereas the latter includes the technologies such as network, data collection and analysis, security, and monitoring and control technologies in the cyber space. Currently, all these elements are being integrated for achieving SMSs in which we can control and analyze various kinds of producing and diagnostic issues in the cyber space without the need for human intervention. In this study, we focus on implementing a production equipment monitoring system related to building a SMS. First, we describe the development of a fog-based gateway system that links physical manufacturing devices with virtual elements. This system also interacts with the cloud server in a multimedia network environment. Second, we explain the proposed network infrastructure to implement a monitoring system operating on a cloud server. Then, we discuss our monitoring applications, and explain the experience of how to apply the ML(Machine Learning) method for predictive diagnostics.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2021.05a
• /
• pp.249-250
• /
• 2021

The use of smart equipment such as drones is increasing in construction sites. In particular, there are frequent cases where two or more drones must be used at the same time. This leads to different considerations than when operating a single unit. This study aims to analyze the requirements to be considered in the case of the operation of drones that monitor fine dust and drones that reduce fine dust in order to reduce fine dust generated in construction sites.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2022.07a
• /
• pp.625-627
• /
• 2022

FEC (Fog/Edge Computing) 환경에서 지연시간 최소화는 로컬과 에지 서버 간의 효율적인 협력을 보장하기 위한 최적의 계산 오프로딩 방법 결정을 통해 실현될 수 있다. 본 논문은 임의의 응용 서비스 실행모듈에 대한 부분 오프로딩 기반의 로컬(모바일 장치)과 에지 서버 간의 협업 경로를 추출하는 방법을 제안한다. 제안 방법은 다중 분기구조를 포함하는 응용 서비스 실행모듈에 대한 부분 오프로딩 기반의 최적 협업 실행경로 추출 방법을 제안한다. 제안 방법은 각 부분 모듈들의 실행위치에 따라 변화되는 지연시간 측정 및 분석에 적용가능하다.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2005.11a
• /
• pp.319-321
• /
• 2005

• Proceedings of the Korean Society for Bio-Environment Control Conference
• /
• 2005.10a
• /
• pp.109-113
• /
• 2005

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2008.04a
• /
• pp.186-187
• /
• 2008

• 한국항공운항학회:학술대회논문집
• /
• 2005.11a
• /
• pp.7-10
• /
• 2005

• 한국항공운항학회:학술대회논문집
• /
• 2005.05a
• /
• pp.87-90
• /
• 2005